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Q: Assume that you have a binomial experiment with p 0.5 and a sample size of 100. The expected value of this distribution is?
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What are the differences between discrete and continuous distribution?

discrete distribution is the distribution that can use the value of a whole number only while continuous distribution is the distribution that can assume any value between two numbers.


If there is a test of 12 true false questions and all answers are guessed what is the mean and standard deviation of correct answers?

We'll assume reasonably that you get a correct answer with probability 0.5. Then the context implies that the number of correct answers is a sum of 12 Bernoulli random variables with p=0.5, which becomes a Binomial distribution with n=12 and p=0.5. Formally: Y(i)~Ber(0.5) => X = Y(1) + ... + Y(12) => X~Bin(12,0.5) The mean for a Binomial distribution is n*p, hence E(X)=12*0.5=6. The variance for a Binomial distribution is n*p*(1-p), hence Var(X)=12*0.5*0.5=3. The standard deviation is calculated as the square root of the variance so SD(X)=3^0.5=1.732.


How do you find the interquartile range when given the mean and standard deviation?

In general you cannot. You will need to know more about the distribution of the variable - you cannot assume that the distribution is uniform or Normal.


What approach to probability is based on a persons degree of belief and hunches that a particular event will happen?

Subjective If you assume particular events will happen with a certain prior distribution, that is Bayesian probability.


What is a contrast between what is expected and reality?

Contrast is a synonym for difference. Expected means when something can be easily predicted or you could assume this would happen. Reality is when is something that could happen but doesn't really include predicting anything. It is more of using common sense to analyze something that could happen.

Related questions

When the population standard deviation is unknown the sampling distribution is equal to what?

The answer will depend on the underlying distribution for the variable. You may not simply assume that the distribution is normal.


What are the differences between discrete and continuous distribution?

discrete distribution is the distribution that can use the value of a whole number only while continuous distribution is the distribution that can assume any value between two numbers.


If there is a test of 12 true false questions and all answers are guessed what is the mean and standard deviation of correct answers?

We'll assume reasonably that you get a correct answer with probability 0.5. Then the context implies that the number of correct answers is a sum of 12 Bernoulli random variables with p=0.5, which becomes a Binomial distribution with n=12 and p=0.5. Formally: Y(i)~Ber(0.5) => X = Y(1) + ... + Y(12) => X~Bin(12,0.5) The mean for a Binomial distribution is n*p, hence E(X)=12*0.5=6. The variance for a Binomial distribution is n*p*(1-p), hence Var(X)=12*0.5*0.5=3. The standard deviation is calculated as the square root of the variance so SD(X)=3^0.5=1.732.


What is the opposite of experience?

There is no direct opposite for the noun experiment (testing). However, the verb experiment could have the opposite words "assume" or "accept" (without experiment).


Why is Maximum Ride The Angle experiment that good?

I would assume you meant "The Angel experiment..."It had suspense, humor, and it had good content... awesome book!


How to find the variance of 36 percent of voters favor a given ballot for groups of 30 voters find the variance for the nunmber who favor the measure?

If you assume a binomial distribution, the variance is n*p*(1-p) where n is the number of voters = 30 p is the probability of support = 0.36 So variance = 30*0.36*0.64 = 6.912


If an event has a 1 in 4 chance of occurring what is the probability of it happening to one individual in a sample of five?

If we assume that the probability of an event occurring is 1 in 4 and that the event occurs to each individual independently, then the probability of the event occurring to one individual is 0.3955. In order to find this probability, we can make a random variable X which follows a Binomial distribution with 5 trials and probability of success 0.25. This makes sense because each trial is independent, the probability of success stays constant for each trial, and there are only two outcomes for each trial. Now you can find the probability by plugging into the probability mass function of the binomial distribution.


What is the smallest measure of central tendency in a positively skewed distribution?

If the distribution is positively skewed distribution, the mean will always be the highest estimate of central tendency and the mode will always be the lowest estimate of central tendency. This is true if we assume the distribution has a single mode.


What is experimental yield?

Experimental yield is the amount of product obtained from a chemical reaction conducted in a laboratory setting. It is compared to the theoretical yield, which is the amount of product that is predicted to be produced based on stoichiometry calculations. Experimental yield is often less than theoretical yield due to factors such as incomplete reactions, side reactions, or losses during purification.


How do you find the interquartile range when given the mean and standard deviation?

In general you cannot. You will need to know more about the distribution of the variable - you cannot assume that the distribution is uniform or Normal.


What are some examples of distribution function?

I will assume that you are asking about probability distribution functions. There are two types: discrete and continuous. Some might argue that a third type exists, which is a mix of discrete and continuous distributions. When representing discrete random variables, the probability distribution is probability mass function or "pmf." For continuous distributions, the theoretical distribution is the probability density function or "pdf." Some textbooks will call pmf's as discrete probability distributions. Common pmf's are binomial, multinomial, uniform discrete and Poisson. Common pdf's are the uniform, normal, log-normal, and exponential. Two common pdf's used in sample size, hypothesis testing and confidence intervals are the "t distribution" and the chi-square. Finally, the F distribution is used in more advanced hypothesis testing and regression.


Why was gold the chosen target for rutherfords experiment?

Gold was chosen for Rutherford's experiment because it is a malleable metal that can be made into extremely thin foils, allowing alpha particles to be passed through easily. Additionally, gold atoms have a high atomic number which results in a denser concentration of positive charge in the nucleus, making it ideal for studying the structure of atoms.